quantumcontrol

Quantum control refers to the use of external controllable fields and interactions to drive the dynamics of quantum systems toward desired objectives. It encompasses theoretical framework and experimental techniques for steering quantum states, populations, and observables via time-dependent Hamiltonians. Core tasks include state preparation, realization of quantum gates, suppression of decoherence, and robust operation under noise.

In closed quantum systems, control is achieved by shaping external fields (electric, magnetic, optical, or magnetic resonance pulses) to manipulate the system’s evolution according to the Schrödinger equation. In open quantum systems, control must account for coupling to the environment, often using techniques from quantum control theory to optimize performance while mitigating dissipation.

Common methods include open-loop optimal control, where a control pulse is numerically optimized to maximize a figure of merit, and closed-loop (adaptive) control, where feedback from measurements informs iterative improvements. Algorithms such as GRAPE (gradient ascent pulse engineering) and CRAB (Chopped Random-Basis) are widely used in quantum chemistry and quantum information. Pulse shaping and composite pulses address bandwidth limitations and robustness.

Applications span quantum information processing, including high-fidelity quantum gates and state transfer; quantum sensing and metrology; chemical reaction control at the quantum level; and nuclear magnetic resonance. In quantum computing, precise control over qubit states and interactions underpins algorithms and error mitigation.

Key challenges include decoherence and noise, control field constraints, scalability to many-body systems, and experimental imperfections. Ongoing research aims to develop theory and hardware that enable reliable, scalable quantum control across diverse platforms such as trapped ions, superconducting circuits, quantum dots, and molecular systems.